NOAA Technical Report NMFS 109

Seasonal Climatologies and

Variability of Eastern Tropical

Pacific Surface Waters

Paul C. Fiedler

U.S. Department of Commerce

April 1992
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NOAA Technical Report NMFS 109

Seasonal Climatologies and

Variability of Eastern Tropical

Pacific Surface Waters

Paul C. Fiedler

April 1992

U.S. DEPARTMENT OF COMMERCE

Barbara Hackman Franklin, Secretary

National Oceanic and Atmospheric Administration

John A. Knauss, Under Secretary for Oceans and Atmosphere

National Marine Fisheries Service

William W. FoxJr., Assistant Administrator for Fisheries
The National Marine Fisheries Service (NMFS) does not approve,

recommend or endorse any proprietary product or proprietary

material mentioned in this publication. No reference shall be made

to NMFS, or to this publication furnished by NMFS, in any advertising or sales promotion which would indicate or imply that NMFS

approves, recommends or endorses any pr~prietary product or proprietary material mentioned herein, or which has as its purpose

an intent to cause directly or indirectly the advertised product to

be used or purchased because of this NMFS publication.

1l
Seasonal Climatologies and Variability

of Eastern Tropical Pacific Surface Waters

PAUL C. FIEDLER

NOAA/NMFS/Southwest Fisheries Science Center

P.O. Box 271

LaJolla, CA 92038

ABSTRACT

Interannual variability caused by the El NiilO-Southern Oscillation in the eastern tropical Pacific Ocean (ETP) is analogous to seasonal variability of comparable magnitude.

Climatological spatial patterns and seasonal variability of physical variables that may

affect the ETP ecosystem are presented and discussed. Surface temperature, surface

salinity, mixed layer depth, thermocline depth, thermocline strength, and surface dynamic height were derived from bathythermograph, hydrocast, and CTD data. Surface

current velocity, divergence, and upwelling velocity were derived from ship drift reports.

Surface wind velocity, wind stress, wind divergence, wind stress curl, and Ekman pumping

velocity were derived from gridded pseudostress data obtained from Florida State University. Seasonal maps of these variables, and their deviations from the annual mean, show

different patterns of variation in Equatorial (S°S-SON) and Tropical Surface Water (SOlS0N). Seasonal shifts in the trade winds, which affect the strength of equatorial

upwelling and the North Equatorial Countercurrent, cause seasonal variations in most

variables. Seasonal and interannual variability of surface temperature, mixed layer depth,

thermocline depth and wind stress were quantified. Surface temperature, mixed layer

depth and thermocline depth, but not local wind stress, are less variable in Tropical

Surface Water than in Equatorial Surface Water. Seasonal and interannual variability are

close to equal in most of the ETP, within factors of 2 or less.

Introduction _

The physical oceanography of the eastern tropical

Pacific Ocean (ETP) was described by Cromwell

(1958) and Wyrtki (1966, 1967), based on sparse obse.rvations by research ships. Research ships and

ships-of-opportunity have made many additional observations since Wyrtki's description. The National

Marine Fisheries Service/Southwest Fisheries Science

Center is currently monitoring the distribution and

variability of dolphin stocks affected by the tuna

purse seine fishery in the ETP. This program requires

a comprehensive review of the climatological distributions and variability of physical oceanographic

variables in the surface waters of the ETP.

The surface waters of the eastern tropical Pacific

Ocean are subject to great variability caused by the El

Nino-Southern Oscillation (ENSO), a 3-6 year cycle

within the coupled ocean-atmosphere system of the

tropical Pacific (Enfield 1989). This interannual variability has profound biological consequences (Walsh

1978; Barber and Chavez 1986). In the past, oceanic

tropical marine ecosystems have been characterized

as exhibiting little or no seasonal variation, probably

due to the paucity of observations (Heinrich 1962;

Sournia 1969). Walsh (1978) did not even consider

the seasonal scale in a review of biological variability

in the eastern tropical Pacific. Yet, seasonal variability

is observed. Seasonal variability of temperature,

wind, sea level, and other physical variables in the

ETP has been described and analyzed by Hickey
2 NOAA Technical Report NMFS 109

80 70

-,

Do" ,

" \.

,.

" -..

100 90

SUBTROPICAL

SURFACE WATER

South o

North Equatorial Countercurrent ----"-_. ----

SUBTROPICAL

o .....SURFACE WATER

20 •• _

North Equatorial Current

10

-10

_- - - - - - - - -.-. - - - - -. - --- ~'tu~orfa' Fro f

-----..... EQUATORIAL •.:..::.:.::••••

Equatorial Current SURFACE WATER Ga~~:'''''''''''

------ ~\(}

-20t:---~r:---<---:'"r::------:T:--"""""---r--""""--",,--""""-r-----,-_--,."""":--.-_-lJ.

~~ 160 150 140 130 120 110

Figure 1

Schematic map of surface currents and water masses in the eastern tropical Pacific Ocean (Wyrtki 1966, 1967).

(1975) and Horel (1982). Primary production and

plankton stocks measured during the 14-month

EASTROPAC expedition of 1967-1968 varied by a

factor of 2 in an apparent seasonal cycle (Blackburn

et al. 1970; Owen and Zeitschel 1970). Reilly (1990)

found variations in distributions of dolphin species,

measured in different seasons in different years, that

are consistent with seasonal environmental variability.

In this report, I examine seasonal variability of physical variables that affect the ETP ecosystem and

quantify relationships between seasonal and

interannual variability. The report is intended primarily as a compilation of available data presented in a

useful format and not a detailed or exhaustive interpretation of the data.

Background _

Surface waters and currents of the ETP (Fig. 1) interact with the northeast and southeast trade winds,

which blow around high pressure centers in the NE

and SE Pacific, on either side of the equatorial low.

The generally westward and equatorward trade winds

drive surface waters to the west in the North and

South Equatorial Currents (NEC, SEC). This transport sets up a downward slope of the sea surface of

about half a meter from west to east across the tropical Pacific. The two trade wind belts converge north

of the equator, between 5° and lOON latitude, in the

Intertropical Convergence Zone (ITCZ), where

winds are weak (the doldrums). The eastward pressure gradient force exceeds the westward wind stress

in the doldrums, so that the North Equatorial Countercurrent (NECC) flows eastward between the NEC

and SEC.

The North and South Equatorial Currents are part

of the subtropical, anticyclonic gyral circulations of

the North and South Pacific. The California and

Peru Currents form the eastern boundary currents of

these gyres. They flow equatorward along the

coasts of Baja California and Peru into the ETP, feeding the eastern, "upstream" ends of the NEC and

SEC.

There are three principal surface water masses in

the ETP: Tropical Surface Water, Subtropical Surface

Water, and Equatorial Surface Water (Fig. 1). Each of

these water masses has characteristic properties determined by climate regimes at local or remote

points of origin. Tropical Surface Water (TSW) is
Fiedler: Climatologies and Variability of Eastern Pacific Surface Waters 3

found in the center of the ETP, along WON. It is the

warmest and least saline water in the ETP. Salinity is

low because rainfall exceeds evaporation beneath the

cloudy and rainy ncz. Cool, high-salinity Subtropical Surface Water (SSW) is found toward the

poleward edges of the ETP, in the subtropical gyres

of the North and South Pacific. Evaporation greatly

exceeds rainfall, and surface salinity is over 36 psu in

the center of the subtropical gyres.

Equatorial Surface Water (ESW) is found between

the Tropical and southern Subtropical Surface Water

masses. It appears as the tongue of anomalously cold

water extending westward along the equator from the

Peruvian coast. Salinity of ESW is intermediate between that of low-salinity TSW and high-salinity SSW.

The cold tongue is maintained either by equatorial

upwelling and advection of cold water from the Peru

Current by the South Equatorial Current (Wyrtki

1981) and by the eastward advection of cold water by

the Equatorial Undercurrent as it rises to the surface

near 95°W (Bryden and Brady 1985).

In addition to the three oceanic surface water

masses, the cool, low-salinity waters of the Peru and

California Currents are also found in the ETP. Peru

Current water is contiguous with ESW. Along the

Central American coast, small and ephemeral water

masses containing cool, recently upwelled water may

be present.

Both coastal upwelling along eastern boundaries

and equatorial upwelling occur in the ETP. Equatorial upwelling is the result of geostrophic divergence

of the wind-driven SEC. The westward component of

the southeast trade winds causes poleward Ekman

transport of surface water on either side of the equator. The effects of upwelling are evident in the

shoaling of the thermocline along the equator and in

the anomalously cold temperature of Equatorial Surface Water. Sverdrup et al. (1942) presented evidence

of surface divergence and upwelling at two sites in

the equatorial current system: along the equator and

between the NECC and NEC at WON. Offshore transport of surface waters and coastal upwelling are

driven by equatorward longshore winds along the

coasts of Baja California and Peru, and by topographically induced offshore winds at several points

along the coast of Central America.

Methods _

The limits of the ETP for this study are 20°S-30oN

latitude and 70o-160oW longitude, to cover the eastern boundary current source waters and the zonal

equatorial current system into the central equatorial

Pacific. Hydrographic data were obtained from two

sources: 1) National Oceanographic Data Center

(NODC) CD-ROM NODC-03: Global Ocean Temperature and Salinity Profiles, vol. 2, Pacific Ocean,

and 2) a Pacific Marine Environmental Laboratory

(PMEL) bathythermograph dataset compiled and edited by Kessler (1990). The NODC data consist of

MBT (mechanical bathythermograph), XBT (expendable bathythermograph), CTD (conductivitytemperature-depth), and oceanographic station (hydrocast) data collected between 1900 and

1990. Radio-message bathythermograph data were

excluded.

NODC screened the CD-ROM data with logical

tests for valid in-water positions and depths and a

crude statistical test: a cast or station was rejected if

temperature (or salinity) at any depth deviated by

more than four standard deviations from the tendegree square mean value. This screen rejected 2.4%

of the MBT/XBT profiles and 2.2% of the CTD/

hydrocast profiles in the entire Pacific Ocean data set

(Topoly et al. 1989). NODC bathythermograph data

collected since 1960 in the ETP study area

(n=134,756) were futher screened by rejecting casts

with temperature inversions >1°C and deep casts

(>400 m) in which the deepest temperature exceeded 20°C (indicating a broken XBT wire). This

preliminary screen rejected 1.5% of the profiles remaining after the NODC screen.

The PMEL bathythermograph data (63,715 casts in

the ETP study area) consist of NODC XBT data

(1967-1985), French-American ship-of-opportunity

XBT data (1979-1987), and Japanese Far Seas Fisheries Research Laboratory MBT data (1970-1980).

Kessler (1990) carefully screened these data for errors. I further screened the NODC MBT/XBT

profiles with a statistical test based on 2 X 5-degree

latitude-longitude means and standard deviations of

the PMEL data: a cast was rejected if surface temperature or 20°C isotherm depth deviated from the mean

by more than 3 standard deviations. This final screen

rejected 7.8% of the NODC profiles remaining after

the preliminary screen. The screened NODC data

consisted of 122,425 profiles. The PMEL data set contained 15,442 additional profiles, for a total of

137,867 MBT and XBT profiles (1960-1990) available for analyses of surface temperature, mixed layer

depth, thermocline depth, and thermocline strength

in the ETP (Fig. A-I).

Mixed layer depth has been defined in various ways

to represent the depth of the wind-mixed (isothermal

or homogeneous) layer at the ocean surface. The

most widely-used definition of mixed layer depth,

and the definition used here, is the depth at which
4 NOAA Technical Report NMFS 109

117W XBT Transect, 18 Dec 1986 - 4 Jan 1987

0

100

E

:E 200 Q.

Q)

0

300

400

-20 -10 0 10 20 30

Latitude

Figure 2

Meridional XBT transect across the eastern tropical Pacific (along approximately 117°W) by the albacore fishing vessel Bald

Eagle, 18 December 1986-4 January 1987, showing the 20°C and 15°C isotherms located in the middle and bottom of the

thermocline, respectively.

temperature is 0.5°C less than surface temperature

(e.g. Wyrtki 1964; Levitus 1982).

The 20°C isotherm is in the middle of the thermocline over most of the tropical Pacific (Fig. 2). Depth

of the 20°C isotherm is conventionally used to represent thermocline depth in the equatorial Pacific

(Donguy and Meyers 1987). It represents the permanent thermocline, not the secondary shallow

thermocline that develops during summer at the subtropical extremes of the ETP and in Peru Current

water (Wyrtki 1966). Where surface temperature is

less than 20°C, thermocline depth is undefined.

I used CTD and hydrocast data from the NODC

data set for analyses of surface salinity and 0/500 db

dynamic height. NODC screens these data somewhat

more thoroughly than the bathythermograph data,

so no additional quality control was attempted here.

Casts for which the first recorded depth exceeded 10

m (2.5% of the total) and hydrocasts collected prior

to 1960 (28.6%) were excluded. This left 18,711

hydrocasts and 8,029 CTD casts in the study area

(1960-1988, Fig. A-I), with 26,149 surface salinity observations and 12,440 profiles with sufficient data to

calculate 0/500db dynamic height. Tsuchiya (1974)

claimed that 500 db is a valid reference level for estimating surface geostrophic flow in the ETP, because

waters deeper than 500 m are relatively homogeneous.

Ship drift reports are from the NODC Surface Current Data Set. Most of these data were provided by the

U. S. Navy Fleet Numerical Oceanography Center,

with some missing data obtained from NODC. For the

study region, there were 229,782 ship drift reports for

the period 1900-1969 (Fig. A-I). Surface current vectors were averaged seasonally on a 2 X 2-degree latitude-longitude grid. Observations were averaged

within ±2 degree latitude and up to ±l0 degrees longitude of each grid point, to resolve the predominantly zonal structure of equatorial surface currents.

Meehl (1982) showed that surface currents estimated

from ship drift were about equal to directly measured

currents from drift buoys or current meters, and

about twice as large as computed geostrophic currents. McPhaden et al. (1991), however, found that

windage can bias ship drift data by up to 3% of the

surface wind speed. Richardson (1989) identified 10-

degree square and monthly blocks of missing data in

the global Surface Current Data Set. Although no

gaps were seen in the seasonal distributions of data in

our study area, it is possible that missing months or

years in some seasonal blocks could confound the patterns of spatial and seasonal variability.

Data were gridded by season on a 2-degree latitude-longitude grid. At each grid point, the mean of

at least 20 observations within 2 degrees or more was

calculated. Normal probability plots of data for representative seasonal grid points indicate that the data

are close to normally distributed in tropical and subtropical waters (Fig. A-2). Although equatorial data

tend to be bimodally distributed due to ENSO variability, the mean and standard deviation appear to be

appropriate measures of central tendency and dispersion for most of the study area. No attempt was made

to correct the bimodality of equatorial data, for instance by treating data from El Nino years separately.

The range of observations around a grid point was

increased in increments of one degree to obtain a

minimum sample size for each mean (n=20 for
Fiedler: Climatologies and Variability of Eastern Pacific Surface Waters 5

bathythermograph and hydrocast data, n=100 for

ship drift data). Thus, local grid resolution decreases

in data-poor regions. A larger minimum sample size

was used for ship drift data because of the high coefficien t of variation of the observations (compare

range and mean in Fig. A-2d). In data-poor regions,

generally south of the equator, the maximum radius

required was 8 degrees for bathythermograph data

and 10 degrees for hydrocast and ship drift data (Fig.

A-3). Within ±I0 degrees longitude of a few grid

points, there were less than 100 ship drift observations, but never less than 25.

The standard deviations (rms deviations) and numbers of observations in grid point samples are plotted

in Figure A-4. Ranges of standard error (rms error)

for 95% of the grid means are 0.04-0.31°C for surface temperature, 0.6-7.0 m for mixed layer depth,

0.8-5.6 m for thermocline depth, 0.01-0.17 psu for

surface salinity, 0.4-3.1 dyn cm for surface dynamic

height, 0.8-5.0 cm S-I for eastward ship drift, and 0.7-

3.6 cm S-I for northward ship drift.

Annual climatologies were computed as averages of

the four seasonal grids, to eliminate bias caused by

non-uniform sampling over seasons. Seasonal variability is illustrated by contour maps of the seasonal

grids and of the seasonal deviations from the climatology (seasonal grid minus climatology).

Surface wind data were obtained as monthly 2 X 2-

degree grids of pseudostress (wind components

multiplied by wind magnitude, m2 S-2 (Legler and

O'Brien 1988) for the period 1961-1989. Pseudostress was converted to wind stress (dyne cm-2 ) using

a constant drag coefficient of 1.4 X 10-3 and an air

density of 1.2 kg m-3•

Several parameters were derived from the gridded

fields of mixed layer depth, isotherm depths, ship

drift, and wind pseudostress or stress. These parameters are thermocline strength, surface current

divergence, upwelling velocity, surface wind divergence, wind stress curl, and Ekman pumping velocity.

Thermocline strength was derived from the 20°

and 15°C isotherm fields as the temperature gradient

between the two isotherms (OC 10m-I). The 15°C isotherm is typically near the bottom of the thermocline

in the tropical Pacific (Fig. 2; Meyers 1979a).

Surface current divergence (au/ax + av/ay, 10-6 S-I)

was calculated from eastward and northward differences across a grid point of x and y components,

respectively, of ship drift averaged between adjacent

grid points. Horizontal transports were calculated by

assuming that the mean surface currents between

grid points, derived from the ship drift data, are uniform through the mixed layer. Upwelling velocity

(10-3 cm S-1, = m d- 1

) through the base of the mixed

layer was calculated from divergence of the horizontal transports.

Surface wind divergence (l0-6 S-I) was calculated in

the same way as surface current divergence. A similar

finite-difference algorithm was used to calculate wind

stress curl or vorticity (vertical component, 10-8 dyne

cm-3):

curl (T) = aT /ax- aT lay, z y x

where Tx and Ty are the x and y components of wind

stress T.

Ekman pumping velocity, or vertical velocity at the

bottom of the Ekman layer (10-3 cm S-1), was calculated from wind stress as follows:

w = curl (T/!)/p , e z IV

where! is the Coriolis parameter (2flsin8, fl=angular

velocity of the earth's rotation, 8=latitude) and Pw is

water density (1000 kg m-3). Ekman pumping velocity

was calculated only for latitudes >6° from the equator: Ekman theory cannot be used to estimate

upwelling near the equator, where the Coriolis force

is zero and cannot balance wind stress. Coastal upwelling was estimated with this equation by setting

T = T = 0 at the coast. x y

Seasonal and interannual variability of surface temperature, mixed layer depth and thermocline depth

were estimated after averaging each variable in bins

of 2 degrees latitude X 5 degrees longitude and twomonth intervals from 1960 through 1989. Seasonal

and interannual standard deviations were calculated

as the standard deviations of bimonthly binned values after subtracting the yearly or bimonthly means

for the bins. Sums of squares of MBT and XBT data

were calculated separately, because Kessler (1990)

noted a deep bias of MBT isotherm depths compared

to XBT depths. Seasonal and interannual standard

deviations were calculated only for bins with data in

at least 15 of the 30 years and 5 of the 6 bimonths.

Seasonal and interannual standard deviations of wind

stress were calculated from the 1961-1989 mon thly

2 X 2-degree grids averaged in bimonths. Standard

deviations of the x and y components were calculated

separately and summed. Thus, wind stress variability

includes variations in both the magnitude and direction of wind stress.

Results _

Annual Climatologies

The mean surface temperature field (Fig. A-5) has a

band of warm water (>27°C) extending zonally across

the ETP north of the equator, centered at SON in the
6 NOAA Technical Report NMFS 109

Mean mixed layer depth increases from about 20-

30 m along the coast to >70 m in the subtropical

gyres (Fig. A-6). Shoaling of mean mixed layer depth

at the poleward extremes of the study area, toward

the centers of the gyres, is the result of high seasonal

variability. Two zonal ridges in mixed layer depth lie

along the equator and looN. East of 120oW, the

mixed layer is most shallow along the equator, but to

the west, it is most shallow along lOON.

Mean thermocline topography is similar to that of

mixed layer depth (Fig. A-6). Thermocline depth increases from 40-60 m along the coast to >150 m in

the subtropical gyres. As for mixed layer depth, thermocline topography consists of a series of zonal

ridges and troughs. I use the traditional names of

ridges ap.d troughs in sea level or surface dynamic

height (Wyrtki 1974) to label the corresponding subsurface features in the thermocline topography:

equatorial surface trough and thermocline ridge,

countercurrent surface ridge and thermocline

trough at 4°N, countercurrent surface trough and

thermocline ridge at lOON. The peak at the eastern

end of the countercurrent thermocline ridge at 900W

is the Costa Rica Dome, a region of strong, localized

upwelling (Wyrtki 1964; Hofmann et al. 1981).

The thermocline is strongest beneath Tropical Surface Water (Fig. A-7). The thermocline is somewhat

weaker beneath Equatorial Surface Water, especially

directly on the equator. Here the Equatorial Undercurrent, a geostrophically balanced, eastward,

subsurface current, lies within the thermocline

(Picaut et al. 1989). The thermocline is weakest beneath SUbtropical Surface Water and in the Gulf of

Panama, where low surface salinity strengthens the

pycnocline beneath the surface layer.

The mean topographies of the thermocline and

sea surface (surface dynamic height, Fig. A-8) are

strongly correlated (Fig. 3, r=0.84). In general, sea

level and depths of isotherms in the thermocline are

highly correlated in the tropical Pacific (Rebert et al.

1985). Although thermocline topography, with an order of magnitude more data points, is better defined

in most of the ETP, the equatorial and countercurrent surface troughs are evident in the mean surface

topography. Spatial variations of surface dynamic

height and thermocline depth reflect the directional

tendencies of the largely zonal, near-surface currents

of the ETP, following simple geostrophic theory. In

the northern hemisphere, the sea surface will be

higher (and the thermocline deeper) to the right of

a current as the observer looks downstream. In the

southern hemisphere, the opposite is true.

The broadest current in the ETP, the South Equatorial Current (SEC), flows westward through the

region, spanning the equator from about lOoS to 4°N

100 150 200 250

Thermocline Depth, m

E 130 u

c

>-

'a 120 ,.;

z:

CI

'i 110 ::c

u

EIV 100 C

>-

C

I) 90 u

IV

-..

::J

CI) 80 ,",0

70

0 50

140 -r-----'----L------J'-----..L...,~-+

west and 15°N along the coast of Central America.

This band is the eastern end of the large warm water

resevoir straddling the equator in the western Pacific.

East of 130oW, the "thermal equator" lies north of

the geographic equator, with the warmest surface water found off the coast of Mexico. The coldest water

in the ETP is off Baja California in the north and

along the coast of Peru in the south. A band of cool

water, the "cold tongue" of Wyrtki (1981), extends

along or slightly south of the equator to the west of

the Galapagos.

The mean surface salinity field is dominated by a

zonal band of low-salinity water along lOON (Fig. A5). Salinity decreases to the east and is very low «32

psu) in the Gulf of Panama. Salinity increases

poleward of this band, except off the coa~t of Baja

California. Oceanic surface water of the highest salinity is found south of lOoS.

The climatological fields of temperature and salinity define the three principal surface water masses in

the ETP (Wyrtki 1966, 1967). The warm, low-salinity

water centered on lOON is Tropical Surface Water

(TSW). The tongue of cool, moderately saline water

along the equator is Equatorial Surface Water (ESW).

High-salinity Subtropical Surface Water (SSW) is in

the subtropical gyres of the orth and South Pacific,

toward the poleward edges of the ETP. The cold, lowsalinity water off Baja California is California Current

Water and the cold, moderately saline water off Peru

is Peru Current Water.

Figure 3

Surface dynamic height (0/500db, dyn cm) versus thermocline depth (m) in the seasonal climatologies. Solid line

represents linear regression (1'=0.84).
Fiedler: Climatologies and Variability of Eastern Pacific Surface Waters 7

along the equatorial surface trough (thermocline

ridge). North of the countercurrent surface trough

at looN, where the sea surface slopes upward to the

north, the North Equatorial Current (NEC) also

flows westward. Along the eastern boundary, the

downward slope of the sea surface (and upward slope

of the thermocline) toward the coasts of Peru and

Baja California reflect the equatorward flow of the

Peru and California Currents. The North Equatorial

Countercurrent, flowing eastward on the southern

slope of the countercurrent thermocline ridge between the NEC and SEC, is resolved in the mean

surface dynamic height field only to the west of

130°W.

Surface currents from ship drift reports (Fig. A-8)

are consistent with the geostrophic flow inferred

from surface dynamic height and thermocline topographies. The strongest flow (up to 0.5 m S-I) is within

the westward South Equatorial Current, between 50S

and 3°N. The westward North Equatorial Current,

north of lOoN, is weaker (about 0.2 m S-I). The North

Equatorial Countercurrent appears in the annual

mean as a weak eastward flow between 5 and looN.

The NECC undergoes substantial seasonal variation

and is stronger in some seasonal climatologies, as will

be seen below. The California and Peru Currents

flow equatorward along the eastern boundaries of

the ETP, with mean speeds of about 0.1 m S-I.

Surface current divergence (Fig. A-g) is strongest

along the equator, between 3°N and 3°S, and along

the coast of Ecuador and Costa Rica. There is a

strong convergence at 4-9°N, between the SEC and

NECC. A strong divergence at lOON, 86°W coincides

with the Costa Rica Dome. Divergence is also strong

along the coast of Ecuador and northern Peru. Weak

divergences occur along the coast of Mexico and, offshore, at some points along lOoS and between lOON

and 20oN. Upwelling velocity, calculated from the divergence of surface transport in the mixed layer, is >1

X 10-3 cm S-1 ("" 1 m d-I) along the equator west of

110oW. Weaker oceanic upwelling occurs in a band

centered on IsoN and south of the equator to the

east of 120oW. Coastal upwelling is strongest off Ecuador and Costa Rica, with weaker upwelling along the

coasts of Mexico and Peru.

The mean surface wind field shows the northeast

and southeast trade winds converging at lOON (Fig.

A-I0). Winds tend to be equatorward and longshore

near the coast and more easterly to the west, reflecting the geostrophic flow of the trade winds around

the North Pacific high pressure center at 35°N,

1400W and the South Pacific high at 30oS, 1000W

(Oort 1983). This pattern of prevailing wind direction is summarized in Figure A-II. The mean surface

wind divergence field shows the strong convergence

of the trade wind belts (Intertropical Convergence

Zone, ITCZ) between 5 and 15°N. Winds are weakly

divergent over most of the remainder of the ETP.

Mean wind stress (and wind speed) is strongest in

two offshore bands to the north of lOON and south of

the equator (Fig. A-ll). Mean wind stress is weakest

east of 1200W and north of the equator. Wind stress

tends to be zonal over the open ocean and more

meridional or longshore in coastal waters, except under the ITCZ. Longshore, equatorward winds blow

along the coasts of Baja California and Peru, driving

offshore transport of surface water and coastal upwelling. A band of weak winds, the doldrums, lies

between the trade wind belts in the ITCZ east of

120°W.

The mean wind stress curl field (Fig. A-12) must be

interpreted with care. In the northern hemisphere,

positive curl is cyclonic. The resulting Ekman transport in the surface layer of the ocean is horizontally

divergent and mass balance is conserved by upwelling of subsurface water. In the southern

hemisphere, negative curl is cyclonic and forces upwelling into the surface layer. Thus, cyclonic wind

stress curl (surface divergence) is found in the ITCZ

at looN, except between 1000 W and 110oW, and just

south of the equator out to 130oW. Anticyclonic

wind stress curl (surface convergence) is found north

and south of the ITCZ in the northern hemisphere

and south of lOoS.

The mean Ekman pumping velocity field (Fig. A12) shows upwelling driven by positive (cyclonic)

wind stress curl under the ITCZ along lOON. The

strong positive curl in this band west of 1300 W does

not result in upwelling because of the strong latitudinal gradient in Coriolis force south of lOON. The

greatest Ekman upwelling velocities are found off the

coast of Costa Rica at the Costa Rica Dome, and

along the coasts of Baja California and Ecuador-Peru.

Seasonal Climatologies and Deviations

Seasonal climatologies of surface temperature (Fig.

A-13a) show that the band of warm Tropical Surface

Water extends across the ETP in all seasons. The

equatorial cold tongue is very weak in March-May.

Surface temperature in much of the ETP varies seasonally by less than ±1°C (Fig. A-13b). Seasonal

variation is greater in equatorial and coastal (Baja

California and Peru Current) upwelling regions and

in northern Subtropical Surface Water north of

20oN. The cool tongue of Equatorial Surface Water,

out to 130oW, is 2-5°C warmer in boreal spring

(March-May) than in fall (September-November).

The nodal (zero deviation) line between seasonal
8 NOAA Technical Report NMFS 109

warming and cooling in the northern and southern

hemispheres represents the "thermal equator" and

lies between lOoN and 100S, but usually north of the

equator.

Surface salinity does not vary seasonally by more

than ±O.l psu, except along the coast of Central

America (especially in the Gulf of Panama) and. in

the low-salinity core of Tropical Surface Water along

lOoN (Fig. A-l4). In these regions, surface salinity is

low in fall (September-November) and high in

spring (March-May).

Mixed layer depth (Fig. A-15) varies seasonally by

±1O m over most of the ETP and ±20-30 m north of

200N and south of l5°S. The mixed layer shoals in

summer and deepens in winter, with a nodal (zero

seasonal deviation) line corresponding to the thermal equator in March-May and SeptemberNovember. The seasonal deviation maps indicate

phase differences in this seasonal change along the

Mexican Coast (lead) and in equatorial waters west of

11OOW (lag).

Thermocline depth (Fig. A-16) undergoes seasonal

deviations of ±20 m only at the poleward extremes of

the ETP. Seasonal variations of ±1O m, associated with

the North Equatorial Countercurrent and equatorial

upwelling, occur between 50S and l5°N. Seasonal

variations in the depths of the countercurrent thermocline trough and ridge are out of phase.

Therefore, the slope between them is weakest in

spring and strongest in fall. Thermocline depth does

not vary seasonally directly beneath the core of the

NECC at 8°N.

Seasonal climatologies of thermocline strength

(Fig. A-17) show a strengthening of the strong

thermocline beneath Tropical Surface Water in

spring (March-May) and a weakening in fall (September-November). This pattern is not coherent

across the ETP. East of l25°W, this strengthening

begins in winter and the weakening begins in

summer. The equatorial thermocline is weakest in

March-May.

Seasonal climatologies and deviations of sea surface dynamic height (Fig. A-18) roughly correspond

to those of thermocline depth. For example, positive

spring and negative fall deviations of the countercurrent surface trough are accompanied by opposing

deviations of the underlying countercurrent thermocline ridge. The meridional sea surface slope

associated with the North Equatorial Countercurrent

west of l300W is much steeper in fall than in spring.

Sea surface slope along the equator, produced by the

piling up of surface water in the western Pacific by

trade winds, is seasonally weak in March-May and

strong in September-November. In contrast, the

zonal sea surface slope associated with the California

Current off Baja California is strong in spring

(March-May) and weak in fall (September-October).

Seasonal variability of surface currents derived

from ship drift reports is greatest between l2°N and

2°S and along the coast of Baja California (Fig. A-19).

The South Equatorial Current and North Equatorial

Countercurrent are strongest in September-November and weakest in March-May, while the California

Current is strongest in March-May and weakest in

September-November. These results are consistent

with the seasonal variability of geostrophic flow inferred from surface dynamic height and thermocline

depth. Note that seasonal variability of the NECC begins east of l200

W, where spring weakening appears

in December-February and fall strengthening appears in June-August. Spring weakening and fall

strengthening then propogate westward in MarchMay and September-November, respectively. Little

seasonal variability in the North Equatorial Current

or Peru Current is evident in the ship drift data.

Seasonal variations of surface current divergence

(Fig. A-20) are difficult to interpret, except in coastal

regions of high mean divergence. The clearest patterns are the winter maxima along the coast of

Mexico and in the region of the Costa Rica Dome

(December-February) and south of the equator off

Ecuador Uune-August). Seasonal variations in

coastal upwelling velocity (Fig. A-2l) are similar to

the patterns in surface divergence. Variations along

the equatorial and countercurrent divergences are

more coherent in the upwelling velocity fields. Equatorial upwelling west of the Galapagos tends to be

stronger in September-February and weaker in

March-August. Downwelling between the SEC and

NECC (along 5°N west of 1100W) is weakest in

March-May and strongest in September-November.

The greatest seasonal variability in surface winds

occurs between l6°N and 4°N (Fig. A-22). The ITCZ

is south of looN in December-May, resulting in

northeasterly seasonal deviations in this band. When

the ITCZ is north of lOoN, in June-November, the

seasonal deviations are southwesterly. As for surface

currents, seasonal changes along looN begin east of

1200W in winter and summer, and propagate to the

west in spring and fall. Moderate seasonal variability

also occurs over the subtropical gyres in the northwest and southwest corners of the study region.

Seasonal variability of surface wind divergence reflects the seasonal migration of the ITCZ between

8° and 12°N (Fig. A-23). Seasonal deviations are

zero along lOoN, the mean position of the ITCZ.

Opposing seasonal deviations of ±1-3 X 1O~ S-1 divergence occur between the equator and 200N. In

addition to variability due to seasonal migration, convergence in the ITCZ, and divergence to the south of
Fiedler: Climatologies and Variability of Eastern Pacific Surface Waters 9

the ITCZ towards the equator, is strongest in fall

(September-November) and weakest in spring

(March-May) .

Surface wind stress in the two regional maxima

north of the ITCZ and south of the equator is greatest in winter-spring and weakest in summer-fall (Fig.

A-24). Seasonal variability of wind stress is greatest

(fO.3 dyne cm-2) at 10-15°N, along the mean northern edge of the ITCZ. Some of the varibility here is

due to seasonal movement of the ITCZ: wind stress is

high in winter-spring (December-May), when the

ITCZ is south of lOoN and this region is exposed to

the full strength of the northeast trades, while wind

stress is low in summer-fall (June-November), when

the ITCZ is north of lOoN. Seasonal variability of

wind stress along the equator is relatively low (fO.l

dyne cm-2 ), but is stronger in June-November than

in December-May.

Seasonal variability of wind stress curl and Ekman

pumping velocity reflect the seasonal migration of

the ITCZ between 8° and 12°N (Figs. A-25, A-26).

Seasonal deviations are zero along looN, the mean

position of the ITCZ. Opposing seasonal deviations

of ±OA X 10-8 dyne cm-3 wind stress curl occur within

5 degrees north and south of lOON. The maximum

curl in the ITCZ is +0.6 X 10-8 dyne cm-3• Cyclonic

(negative) wind stress curl south of the equator is

weakest in December-February and strongest in

June-August. Seasonal variability of Ekman pumping

velocity is also affected by migration of the ITCZ, but

the pattern is complicated by the strong gradient in

the Coriolis parameter (1) near the equator. Coastal

upwelling estimated by Ekman theory is strongest in

March-May (spring) off Baja California and in JuneNovember (winter-spring) off Ecuador and northern

Peru.

Seasonal/Interannual Variability

Surface temperature variability is very low (<1 0c)

in Tropical and southern Subtropical Surface Water,

both seasonally and interannually (Fig. A-27). Seasonal variability is low across the equator to the west

of 1400W, from 15°N to 15°S. Seasonal and

interannual variability are high (l-2°C) in Equatorial

Surface Water, in the Peru Current, and off Baja California. High seasonal variability also occurs in

northern Subtropical Surface Water north of Hawaii.

Interannual variability exceeds seasonal variability in

Tropical Surface Water and in Equatorial Surface Water west of 1200

W, where variability on both time

scales is low and mean surface temperature is high

(see Fig. A-5). Seasonal variability exceeds interannual variability both in coastal Peru and California Current water and in Subtropical Surface

Waters.

Mixed layer depth variability increases to the west,

as does mean mixed layer depth. Variability is greatest in Subtropical Surface Water north of 200N and

south of 15°S, and along the equator west of 135°W.

Seasonal variability exceeds interannual variability,

except in Tropical Surface Water east of 1200W and

in Equatorial Surface Water west of the Galapagos.

Variability of thermocline depth is less than the

variability of mixed layer depth, especially seasonally

(Fig. A-29). Thermocline depth variability is greatest,

both seasonally and interannually, in Subtropical Surface Water north of 200N. Interannual variability is

low in Tropical Surface Water and higher in Equatorial Surface Water. Seasonal variability is low in a

band along 17°N, corresponding to the north equatorial thermocline trough (Fig. A-6). There are three

zonal bands in seasonal variability to the south of this

band, most obvious to the east of 1300W: a local

maximum along 12°N, a minimum along 8°N, and a

maximum along 4°N. This pattern reflects the seasonal variation in the slope of the thermocline

beneath the North Equatorial Countercurrent caused by opposing variations in depth of

the countercurrent thermocline ridge and trough to

the north and south of 8°N. Seasonal variability exceeds interannual variability only in this region and

in Subtropical Surface Water north of 18°N (123-

146°W).

Wind stress variability increases from east to west

(Fig. A-30), as does mean wind stress (Fig. A-ll). Seasonal variability is very high along lOON west of

1l00W, owing to seasonal movement of the ITCZ.

Seasonal variability exceeds interannual variability by

more than a factor of two in this region east of

1300W. Seasonal and interannual variability of wind

stress along the equator is low compared with variability at tropical and subtropical latitudes.

Discussion _

A T-S diagram of eastern tropical Pacific surface waters, using seasonal grid means, shows the principal

oceanic surface water masses and eastern boundary

current waters (Fig. 4). Tropical Surface Water

(TSW) is the warmest, least saline water mass in the

ETP. This warm water provides the energy to drive

the Hadley cells (including trade winds) over the

tropical ocean in both hemispheres (Bjerknes 1966).

The "thermal equator" in the ETP lies north of the

geographical equator, in Tropical Surface Water.

Temperature of TSW varies little, either seasonally or

interannually. The warm surface temperature and
10 NOAA Technical Report NMFS 109

.:.>;"

0.5 1.0 1.5

O--r-~~"---"--r-""-''''''--'--''----r-'-----'--,---,---+

0.0

...,.

E

.s: 100

Q.

lD

C

Ii

>-

10

...I

'0

lD 50 x

:i

35 36 37

....

33 34

30

28

$>

• 26

..

10

.. 24 lD

Q.

E

22 Ql

u

10

..... 20 ::J

C/)

18

16

32

Surface Salinity, psu Wind Stress, dyn cm-z

Figure 4

Surface temperature (OC) vs. surface salinity (psu) in seasonal climatologies. TSW = Tropical Surface Water; ESW =

Equatorial Surface Water; SSW = Subtropical Surfac.e Water; PCW = Peru Current Water; CCW = California Current

Water (Wyrtki 1966, 1967).

Figure 5

Mixed layer depth (m) versus wind stress (dyne cm-2) in

seasonal climatologies. Solid line represents linear

regression (r=0.47).

low variability of TSW results in a high degree of

thermal stratification and a strong, shallow thermocline. The North Equatorial Countercurrent flows

eastward through the core of the TSW, beneath the

Intertropical Convergence Zone (ITCZ), where the

northeast and southeast tradewinds converge and

westward wind stress is at a minimum.

The surface salinity minimum in Tropical Surface

Water lies under the ITCZ and is most pronounced

in fall. The distribution of rainfall in the tropical Pacific has a pronounced maximum at the ITCZ, with a

seasonal maximum in July and August (Dorman and

Bourke 1979). Surface wind convergence in the ITCZ

is maximum in fall (Fig. A-23a). Rainfall and cloudiness (reduced evaporation) in this convergence

produces the surface salinity minimum. The strong,

shallow thermocline beneath the surface layer limits

mixing of fresh water at the surface with deeper,

more saline water.

Mixed layer depth is correlated with wind stress on

the sea surface (r=0.47 in the seasonal climatol<;>gies,

Fig. 5). Wind mixing is theoretically proportional to

(wind speed)3 and not wind stress or (wind speed)2.

However, log-transformation yields a linear regression exponent of 0.48 (r=0.53), meaning that mixed

layer depth is proportional to (wind speed) I. Wind

mixing cannot explain all the variability in mixed

layer depth: the mixed layer is deepest at intermediate values of wind stress. This occurs at the poleward

extremes of the study area, where seasonal variability

of mixed layer depth (Fig. A-28) and net surface heat

flux (Weare et al. 1980) is greatest. Seasonal variability of surface temperature and thermocline depth is

also high in northern Subtropical Surface Water

north of 20oN, presumably owing to the variability in

heat flux.

Seasonal north-south shifts of the ITCZ result in

local changes in the strength and direction of trade

winds. Changes in local wind stress cause variations

in wind-driven surface currents and in surface dynamic height and thermocline depth through local

Ekman dynamics. Ekman pumping explains most of

the seasonal thermocline depth variability in the ETP

(Meyers 1979b; Kessler 1990). The most prominent

signal is the oscillation across the NECC. Wind stress

curl is positive (cyclonic) over the countercurrent

thermocline ridge at lOON, causing Ekman upwelling. Wind stress curl over the countercurrent

thermocline trough at 5°N is negative (anticyclonic),

causing Ekman downwelling. This north-south gradien t in wind stress curl sets up the slopes in

thermocline depth and surface dynamic height

across the NECC. As the ITCZ migrates from its

northern extreme in fall to its southern extreme in

spring, the gradients in wind stress curl and Ekman

pumping velocity weaken, thermocline and sea sur-
0+-----1---'-----''--_-'-__.1....-_-+

20

Fiedler: Climatologies and Variability of Eastern Pacific Surface Waters II

generally warm temperatures and low nutrient concentrations suggest that the effects of upwelling do

not reach the surface (Cromwell 1953). The seasonal

climatologies of surface divergence from ship drift

show that divergence is weak and discontinuous in

the countercurrent divergence, compared to the

equatorial divergence. Upwelling rates are 0.5-2.0 X

10-3 cm S-1 along the equator, but generally <0.2 X

10-3 cm S-I in the countercurrent divergence (up to

0.6 X 10-3 cm Sl at the Costa Rica Dome in winter).

Ekman theory gives upwelling rates of about 0.1 X

10-3 cm S-l due to cyclonic wind stress curl along

lOoN, with a peak of 0.2 X 10-3 cm S-1 in winter at the

Costa Rica Dome, compared to coastal upwelling

rates off Peru and Ecuador of >0.5 cm S-I. Estimates

of vertical velocities at the base of the mixed layer

along the equator in the eastern Pacific, from indirect measurement (Halpern et al. 1989), mass

budgets (Wyrtki 1981; Quay et al. 1983), and threedimensional general circulation models (Bryden and

Brady 1985; Philander et al. 1987), range between 0.3

and 5.0 X 10-3 cm S-I. Thus, upwelling rates in the

countercurrent divergence along lOON average about

10% (never more than 25%) of equatorial or coastal

upwelling rates in the ETP.

Equatorial Surface Water (ESW) is the coldest oceanic water mass in the ETP (Fig. 4). Surface

temperature variability is high, both seasonally and

interannually, in these waters. Interannual variability

of thermocline depth is also high. However, variability of local wind stress is low, indicating remote

forcing. EI Nino - Southern Oscillation (ENSO) variability in zonal wind stress in the central and western

equatorial Pacific, and the resulting sea surface and

thermocline slopes along the equator, cause

interannual variability in the temperature and thickness of Equatorial Surface Water (Wyrtki 1985).

Seasonal variability of the temperature of ESW is

only partially related to wind-driven upwelling and its

effects on thermocline depth. The equatorial thermocline shoals in March-May when wind stress is low,

zonal sea surface slope is reduced, and ESW is warmest. Conflicting theories suggest that the average state

of the ESW cold tongue is maintained either by equatorial upwelling and advection of cold water from the

Peru Current by the SEC (Wyrtki 1981) or by the

eastward advection of cold water by the Equatorial

Undercurrent as it rises to the surface near 95°W

(Bryden and Brady 1985). Whichever mechanism

may be correct for the average state, advection of

water by the SEC may play an important role in variations of surface temperature in the cold tongue.

Observations show that seasonal temperature variations are larger near the coast (Fig. A-27) and that

the phase of the variations propagates westward from

15

CCR

o 5 10

latitude

115-140W

-5

Warch-Way

-- September-November

150+---.---~---r---""T'""---r---+

-10

50

Q.

•

.E

U

o 100

•

f=

90-115W

0

Warch-Way

-- September-November

E ER CCR .....,

£ 50 Q. .' • ..' 0

•.E

U

0

E 100 ...

•

I150

-10 -5 0 5 10 15 20

latitude

Figure 6

Seasonal average meridional profiles of thermocline (20°C

isotherm) depth. ER = equatorial ridge; CCT = countercurrent trough; CCR= countercurrent ridge.

face slopes flatten, and flow of the NECC diminishes.

Meridional sections of thermocline depth (Fig. 6)

show this seasonal variability in thermocline slope.

The slope is weaker, almost flat in spring, east of

ll5°W. Seasonal north-south migration of the countercurrent thermocline ridge, and to a lesser extent

of the trough at 4°N, causes a meander in the NECC

(Kessler and Taft 1987).

Sverdrup, Johnson, and Fleming (1942) presented

evidence of surface divergence and upwelling at two

sites in the equatorial current system: along the equator (equatorial divergence) and between the NECC

and NEC at lOON (countercurrent divergence). The

countercurrent thermocline ridge is evidence of upwelling in the countercurrent divergence, although
12 NOAA Technical Report NMFS 109

the coast (Horel 1982). For example, the coldest surface temperature relative to the annual mean occurs

in August-September near the coast and in November at 1400 W (Horel 1982).

The South Equatorial Current (especially north of

the equator) and North Equatorial Countercurrent

vary synchronously in the ETP. Both currents are

weak, or even absent, in spring and strong in fall

(Fig. A-19). This is consistent with earlier analyses of

ship drift (Wyrtki 1966) and dynamic topography

(Wyrtki 1975). In the central Pacific, however, the

NECC varies in phase with the North Equatorial Current and in opposition to the SEC (Wyrtki 1974;

Kessler and Taft 1987). Here, the NECC does not

peak until December (Wyrtki 1974), consisten t wi th

the westward propagation of seasonal change in surface winds and surface currents observed in the ETP.

The westward propagation of seasonal deviations

(change of phase in the annual cycle) of surface

winds in the ITCZ seen in Fig. A-22b was also observed by Horel (1982).

Eastern boundary currents also vary seasonally in

the ETP. Along the coast of Baja California,

equatorward winds are strong in spring (March-May)

and weak in fall (September-November, Fig. A-22).

Weaker offshore Ekman transport of surface water in

fall reduces the zonal slope of the sea surface adjacent to the coast (Fig. A-18). Therefore, the

California Current is strong in spring and weak in fall

(Fig. A-19). Northeast trade winds blowing across

southern Mexico and Central America are strongest

in winter (December-February, Fig. A-22). These

winds drive coastal upwelling, especially in the Gulf

of Tehuantepec at 15°N, 95°W (McCreary et al.

1989), where the winter surface temperature deviation is <-1°C. In contrast, the variability of winds and

surface currents in the Peru Current is very low in

the seasonal climatologies.

Interannual variability in the ETP is analogous, in

some respects, to seasonal variability (Philander

1989). When the southeast trade winds are weak

(March-April or El Nino years), the South Equatorial

Current is weak, the equatorial thermocline slope is

flatter, and Equatorial Surface Water is warm. When

the southeast trades are strong (September-October

or La Nina years), the South Equatorial Current is

strong, the equatorial thermocline slope is steeper,

and Equatorial Surface Water is cold. A zonal redistribution of surface waters occurs on both time scales.

Interannual variability of the North Equatorial Countercurrent, however, is not analogous to seasonal

variability. During EI Nino, when the southeast trades

are weak, the NECC intensifies out of phase with

the weakened SEC. The resulting eastward transport

of warm waters causes warming and thermocline

depression in both the Tropical and Equatorial Surface Water masses of the ETP.

In general, seasonal variability of physical oceanographic variables in the eastern tropical Pacific

Ocean is comparable, in magnitude and relationships

among most variables, to interannual variability associated with the El Nino-Southern Oscillation.

Patterns and magnitude of environmental variability

differ significantly among surface water masses, and

thus among biological habitats. These results should

be considered in studies of biological responses of

populations and ecosystems to environmental variability in this important region of the world's oceans.

Acknowledgments _

I thank James Stricherz and James O'Brien of Florida

State University for providing the gridded wind data,

Craig Nelson of NOAA/Center for Ocean Analysis

and Prediction for providing ship drift data, Norman

Hall of NOAA/NOS/National Ocean Data Center for

assistance with data, and Dave Behringer of NOAA/

NWS/Climate Analysis Center for advice and software.

Citations _

Barber, R.T. and F.P. Chavez.

1986. Ocean variability in relation to living resources during

the 1982-83 EI Nino. Nature 319:279-285.

Bjerknes, J.

1966. A possible response of the atmospheric Hadley circulation to equatorial anomalies of ocean temperature. Tellus

4:820-829.

Blackburn, M., R.M. Laurs, R.W. Owen, and B. Zeitsche!.

1970. Seasonal and areal changes in standing stocks of phytoplankton, zooplankton and micronekton in the eastern

tropical Pacific. Mar. BioI. 7:14-31.

Bryden, H.L., and E.C. Brady.

1985. Diagnostic model of the three-dimensional circulation

in the upper equatorial Pacific Ocean. J. Phys. Oceanogr.

15: 1255-1273.

Cromwell, T.

1953. Circulation in a meridional plane in the central equatorial Pacific. J. Mar. Res. 12:196-213.

1958. Thermocline topography, horizontal currents, and

"ridging'" in the eastern tropical Pacific. Bull. Inter- American Tropical Tuna Commission III:135-164.

Donguy,J.R., and G. Meyers.

1987. Observed and modelled topography of the 20°C isotherm in the tropical Pacific. Oceano!. Acta 10:41-48.

Dorman, C.E., and R.H. Bourke.

1979. Precipitation over the Pacific Ocean, 30 0 S to

600 N. Mon. Weather Rev. 107:896-910.

Enfield, D.B.

1989. EI Nino, past and present. Rev. Geophys. 27:159-187.
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Halpern, D., R.A. Knox, D.S. Luther, and S.G.H. Philander.

1989. Estimates of equatorial upwelling between 140° and

1100W during 1984. J. Geophys. Res. 94:8018-8020.

Heinrich, A.K.

1962. The life histories of plankton animals and seasonal

cycles of plankton communities in the oceans. J. Cons.

Perm. Intern. Explor. Mer 27:15-24.

Hickey, B.

1975. The relationship between fluctuations in sea level,

wind stress and sea surface temperature in the equatorial

Pacific. J. Phys. Oceanogr. 5:460-475.

Hofmann, E.E., Aj. Busalacchi, andJj. O'Brien.

1981. Wind generation of the Costa Rica Dome. Science

214:552-554.

Horel,J.D.

1982. On the annual cycle of the tropical Pacific atmosphere

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Kessler, W.S.

1990. Observations of long Rossby waves in the northern

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Kessler, W.S., and B.A. Taft.

1987. Dynamic heights and zonal geostrophic transports in

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1988. Tropical Pacific wind stress analysis for TOGA. In

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1982. Climatological atlas of the world ocean. NOAA Professional Paper No. 13, 173 p.

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1982. Characteristics of surface curren t flow inferred from a

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Meyers, G.

1979a. Annual variation in the slope of the 14°C isotherm

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1983. Global atmospheric circulation statistics, 1958-1973.

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1990. Seasonal changes in distribution and habitat differences among dolphins in the eastern tropical Pacific. Mar.

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1989. Worldwide ship drift distributions identify missing

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Fiedler: Climatologies and Variability of Eastern Pacific Surface Waters 15

Appendix

Observa.tions 30

20

10

o

150 140 130 120 110 llO 80 70

70

",' ..;

! . . j. 4.'

'r i',

:,:

":t i

W ' .

-if:'

L.

.;::...

':,.

.( .

.. ~.

...::.: . -_.,' '.~

20

._. . :., ...... -20+:.i...~-...;··'""·;:·_--" ......-...;.....;'-~.:-"T""-..:...--r--~-'-i,--:;....--,-..;.,-;--"T""-~_.:.....,...- ......:..:.:::....;1j. 160 150 1M) 130 120 110 100 90 80

-10

Figure A-I

(Top) XBT and MBT

(bathythermograph) observations, 1960-1990, in

combined PMEL (Kessler

1990) and NODC data set,

n = 137,867. (Middle) hydrographic stations (bottle cast

and STD), 1960-1988, in

NODC data set, n = 26,149.

(Bottom) ship drift reports,

1900-1969, n=229,782.
o 50 100 150 200 250

Thermocline Depth, m

Figure A-2a

Normal probability plots of surface temperature, mixed layer depth, and thermocline depth at representative grid points

in September-November: E = Equatorial (OON,lOOOW); T = Tropical (looN,llOOW); and S = Subtropical (200N,1500W).

Local grid resolution = 2 degrees.
Fiedler: Climatologies and Variability of Eastern Pacific Surface Waters 17

3

T E 6 6 2

lit

.3

1

I..

0 0 Z

'U

..•

u -1 •

a.

• E

W E

-2 T s T E

-3

33 33 34 34 35 35 36 80 90 100 110 120 130 140

Surface Salinity. P8U Surface Dynamic Height, dyn em

FigureA-2b

Normal probability plots of surface salinity and surface dynamic height (O/500db) at representative grid points in

September-November: E = Equatorial (OON,IOOOW); T = Tropical (IOON,llOOW); and S = Subtropical (200 N,1500W). Local

grid resolution for surface salinity = 3 degrees. Local grid resolution for surface dynamic height = 4(E), 6(T), and 3(S)

degrees.

50 100

ea8tward Ship Drift. em 8- Northward Ship Drift, em .-1 1

3

2

.3•

1

"i

E..

0

Z 0

'U

..•

u -1

a.

•

w

•

-2

T

-3

-150 -100 -50 0 50 100 150-100 -50 0

FigureA-2c

Normal probability plots of ship drift at representative grid points in September-November: E = Equatorial (OON,IOOOW);

T = Tropical (looN,llOOW); and S = Subtropical (200N,1500W). Local grid resolution = 3(E), 5(T), and 2(S) degrees

longitude. .
BATHYTHERMOGRAPH GRIDS -

00

z

a::

;;l

-

<::>

<=l

z

;;3

n'

e.

<'D

'1:l

o

.....

90 80 70

.

..

3 . 3 .. 3

33" 3

'33333··3

334444333

....

100

3

33

3

3

3

3

3 3

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3344333

33444333

33443

... 33

333

33

33 .

333

3333

33333

33

3333333'3

3~5544333

334443

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333

33 .•

301' ••.••.•• + + + •••••

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++++++ ••• + + + + ••• 20~+ ... + •••• • + • • • • • • • • • • • • •.•.. 3 .•. .3

...... 10r.••••..... + •

· .

·.

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33 3 3 .. 33 3

-10~3 •.

333 .

33333

.... ...

...

.

...

3

33

3 3

333

3 3 3 3

333333

.• 34333333'" 333333'" 3

3 44 4 433 3 44433333 44 44443

3

. 3

33' .. 33

333" ..

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3443······ 3

33·· •• ·333 •••••• 3

'33433

3443

..

.

·... ·..

·.. "

·.. 10

301' • •• . .••• + •

• •••••••• + • • •••• + • •• ++++ •••

+ + + + ••• 2.0-1+ + + •

·... o

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33

33

3'3"33

4333·33

-10~4 3 3 3 3 3 •• 3

'3 • 33

90 80 70

. . ..

12.0 110 100

• 3

3 3 3

130

• ••

.. ....

140

.... .... ••••0 • 3 •...•.•..••••••••••••••

·3333····3

33343·333

3 344333· 3· 33 3" .•....•..,

•• 3·3 ·333·' .+ •• 33 344333.+,

3433 3'34433 .. + 3343·3333 33·3443333'

344443334434444445555543 -

150

3°1" •••.. .•• + +

1* • •• • • • • •• + • • • • • • • .+ ••• ++ ••••

++++++.. .•

+ + + + •• 2.0~+ + + • . . . . •

• + + •

...... 3 •••••

10-13

... o

33

333'333

4343'33 ••

-1014 4 4 4 3

43443

3334

3

90 80 70

33

....

100

3

3 3

3 •

110

..

12.0

3

3

333

130

· ... · .. ·.... . 3

33333 ..

1..0

333333333 33

3333333333 •• "3·3

33344443 .. ·33· ·333

3333333" 33 .. 3·33333

433······ 3 333- '3-344443

333···· ·33 ·333343333·3444433

·····3333· . 33333333333' 3455533

.. 33433 ··33444333344333456654333

33343"'33444444444554444577665443

150

301! • • . . ! .•• +*+••• : ......... ! .. ,. • •••••• + . • ••• + + •••• '++++++ •• ·3 1++++ ••.. 3

2.0~+ + + •

• + + • · . · . · . 10 ·..... ·.....

• • ·.... 01:

3

3" • 3

3 3 3 3 3

-10~3 3 3 •.

5333 •

43333

3

-2.01Y . . . 3 Y 3 " .. " f .. " . . y.. ;, P P 9 ; ;, ;, P ? pop p ? p p P Q 9 I I P P 9 • , 4 4 ,.

160

Figure A-3a

Grid sample size and local resolution for bathythermograph data (surface temperature, mixed layer depth and thermocline depth). For grid points with sufficient

observations within a radius of 2 degrees: ~20 ("), ;::100 (*), or ~500 (+). For grid points with <20 observations within a radius of 2 degrees, number equals radius

in degrees within which ~20.
SALINITY GRIDS

-

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e:

C'l

[

o

CIS.

'"§

Co

f

5:

o

.....

Cl

Si

n

J

70

70

80

80

90

90

100

100

110

110

120

120

130

140 130

150 140

150

33333.34333

··334343·333343····

•. 34554333444433'"

•••.. 355655445454433"

20+ ••• 3 3 3 3 5 6 6 6 6 6 6 5 4 4 4 3 . 3 4 3

3 •• 3 3 3 3 3 5 7 7 7 7 7 7 5 4 3 4 3 '.3 4 4 3 3 3

3 •.• ·• 33565557754344345433' 33

3' 3333335533457665544454"33'

3·3 '354"357876555553"33·33

10-(3 • 3 3 4 5 5 3 • 3 5 7 8 7 7 6 5 5 5 4 3 . 3 3 3 3 4 3

3'3 356554566987644543' 33343

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3 . 3 3 5 5 5 4 5 5 7 9 7 6 6 5 4 3 4.4 3 .. 3 .. 4 3

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0-(3 • 3 3 5 5 3 . 3 5 7 8 6 6 5 5 3 3 3 4 3 . . • . • 4 3

3'3' 355333578655544443 '33343

43333356555678766555553333343"'33

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-10-(8 8 7 5 3 3 5 7 9 108 6 5 5 5 5 3 • 3 4 •• 4 5 4 3 4 4 3

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9 7 5 3 3 5 7 9 108 6 5 4 4 5 4 3 3 3 3 4 5 5 4 4 4 3 3 3 3 3 ••

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9 7 5 4 3 3 5 7 9 108 7 6 5 5 5 5 4 4 4 •• 4 6 7 6 6 5 5 5 6 6 6 4 3

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10-(4 3 3 3' 3 4 4 3 .. 3 3 4 5 0 6 5 5 4 4 5 4 3 3 3 4 4 4 3 . 3 3 3 3 3

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3.3.333553' 33546555433333 333433

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-10-(8 7 7 5 3 3 3 5 5 5 6 6 8 9 109 8 7 6 5 6 6 8 II 6 5 4 4 5 43 .

9 8 7 5 4 4 4 5 5 5 6 7 8 10 106 7 6 6 5 6 8 8 6 4 4 4 4 4 3 3 •. • •

9 7 5 4 4 3 5 5 5 6 7 910 108 7 7 7 7 8 8 6 4 3 • 3 3 3 3 3 3 .•

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80 70

Jun-Aug

140 130 120 110 100 90

...... oil ••••••

150

53

43

3 •

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9 7 5 4 3 4 5 7 9 9 8 8 910 109 8 0 5 4 4 3 ••

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09 7 5 3 • 3 5 7 7 7 7 7 7 7 5 4 4 5 5 4 4 5 7 8 10109 7 5 4 4 3 3 4 3 4 3 3 . • •

9 7 5 3 • 3 5 6 • 8 8 8 7 7 5 5 4 5 5 4 4 5 7 810 9 7 6 4 4 3 3 4 3 4 3 3 .• •

08 7 5 3 • 3 5 6 5 6 8 6 6 7 5 5 5 5 4 3 4 5 6 810 9 7 6 5 4 4 3 3 4 5 4 3 3 3 •

9 7 5 3 3 4 5 7 6 8 8 6 7 7 6 6 6 5 5 4 5 6 7 910 108 0 5 4 4 3 3 5 5 6 5 4 4 3 3

-20-t 9!! 7 II Ul0 lpA877 P 33'" -20~ 10877 P 70 flO 1010 91 §ll q 77 7 qq .. ". 180 . ISO l.lo 130 120 ';0 100 90 80 70 ISO I I i

-10

Figure A-3b

Grid sample size and local resolution for surface salinity data. For grid points with sufficient observations within a radius of 2 degrees: 11>-20 (-) or 11>-100 (*). For

grid points with <20 observations within a radius of 2 degrees, number equals radius in degrees within which 11>-20. Missing grid points had insufficient observations

within a radius of 10 degrees.
SURFACE DYNAMIC HEIGHT GRIDS

o

z

-

o

""

z

l")

[

g.

'tl

o

::!.

100 90 80 70 150 140 130 120 110

4333

4 •

3 .

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3 333334554457799765676544445433 33 '45 ... 335779986677653345543333456'

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3 3 3566667899887777543 356543355543344

3 3 3565558797766567543 35654 ... 34444 434'

3 3 3554345787765457543 34554433333 33

0-\3 3 3 5 5 3 3 3 5 7 8 7 7 6 5 5 5 6 5 4 3 . 4 5 5 4 4 • • . 3 • 3

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7 6 6 5 3 3 5 7 9109 9 9 9 9 9 8 6 5 6 7 5 4 3 3 4 5 7 6 6 4 4 ... 4 4 4

8 8 7 5 3 3 5 7 9 108 6 5 6 7 5 4 3 3 4 5 6 6 6 5 5 5 5 5 4

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9753 3579 10865555543344566665554443

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9 7 5 4 4 4 5 7 9 109 8 7 7 7 6 6 5 4 4 4 5 5 6 8 8 7 7 7 7 7 7 6 5 3

30

-10

30

34553_3433'" 3

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3" 3356555543455443'

••• 335677765566754433

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3 333 3567998887776444443"34'

3 3 3 4 6 7 910109 8 7 7 7 6 4 3 4 5 5 3 3 3 3 3

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1,0,3 3 3 •• 3 5 6 8 9 9 9 9 7 6 7 7 6 5 4 4 5 5 3 3 3 4 4 4 5 4 4 4 3 . •

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0-\3 • • •. 3 4 4 5 7 9 9 9 8 7 8 7 6 4 3 3 4 5 4 4 4 5 5 4 3 4 3 . • . .

3' 333 3556791098888643356554553333" 33

43333 356789 998876544567666544443343

6 5 4 4 3 • 3 5 7 8 8 10109 9 8 8 7 6 5 5 5 6 6 8 8 8 7 6 5 5 4 4 4 4 5 4

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09753 .35788878887876778910 10986555565433

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9 7 5 3 . 3 5 6 7 6 6 6 7 7 7 7 8 7 7 8 9 108 7 6 5 5 6 6 7 6 5 4 3 3

9 7 5 3 3 4 5 7 7 7 6 7 7 7 8 8 8 8 91010 109 8 7 5 6 7 7 8 7 6 5 5 3 3 -20~, 9 7 6 5 Y5 6 7 6 q7 7 8 8 ? 9 9 9 i i ? 8 7 7 8 q8 8 8 7 t 5 4 3 .,. -201, 9 8 6 6 Y6 7 8 9 , i 109 9 ? 8 7 7 6 ? 5 6 6 7 t 8 9 8 8 q8 8 8 7 t 5 4 3 • ,.

160 150 140 130 120 110 100 90 80 70 160

100 90 80 70 150 140 130 120 110

30 3 ··44443·.343

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433' 333553' 34678877543443' 33344433'"

443' 333553335687987565553335555444333

6 4 4 4 3 3 3 5 6 5 4 5 6 7 9 9 109 8 7 8 7 7 5 4 4 4 6 7 7 6 5 5 5 5 4 4

7 6 5 5 3 3 3 5 7 6 6 6 7 8 910 109 9 9 9 7 6 5 5 5 7 7 8 7 7 6 6 5 6 4 3

-10-\8 7 7 5 4 3 4 5 7 7 7 7 8 9 9 8 7 6 6 6 7 8 8 8 6 6 a 6 6 4 .

9 9 7 5 4 4 4 5 7 8 8 8 910 109 7 6 6 6 7 8 9 8 7 7 a 5 5 4 3

9 7 5 4 4 4 5 7 8 8 810 . 109 7 7 7 7 8 9 7 7 6 a 5 a 5 4 3 3 3

9 7 5 4 5 4 5 7 8 910 9 9 8 8 9 9 9 8 7 7 7 6 a 8 5 5 5 3

... _.~ .• _, .• _ ,97656567910 101010101099988777765433

Jun-Aug

20

30

-10

·44333,.'433"'3

'3 .. 334343" 33443"

3···355554334556433

.33445776655667644333' '4

3334567888777886555544445

3 .. 333456891099991086666666566 S 4 . 3 4 3 4 4 5 7 810 10 108 6 6 6 6 7 7 7 7 6 5 4 3

43343345689 109766777775543'357

4 3 3 3 3 3 3 5 6 8 9 109 8 8 7 7 7 7 7 6 5 5 5 4 4 4 6 7 8 91

10-\4 3 3 3 . . 3 5 6 8 9 10 109 8 7 7 7 7 6 5 5 5 5 6 6 5 6 7 7 8 8 8

4 4 3 3 . . 3 5 7 7 9 9 9 9 10109 9 8 8 8 8 7 5 4 4 4 5 7 6 6 7 7 7 7 7 6 6

3 3 3 4 3 3 4 5 6 7 7 7 7 8 9 9 8 8 7 7 8 7 7 5 3 3 4 5 7 6 6 7 6 6 7 6 5 4 4 5 6 8'

3333333565556799987676653 3566555566433 ... 68:

3333333554345787887767653 35555434444' 46

0-\3 3 3 4 3 3 3 5 5 4 3 3 5 6 8 8 8 7 7 7 6 7 6 5 3 . . 4 5 5 5 4 3 3 3 3 4 4

3334333554345686887867553'35556433434' 3

5445333565555787988877653'35666555554'

6 6 5 5 4 3 3 5 7 7 6 7 7 8 9 8 109 9 9 8 7 7 5 4 4 4 5 7 7 7 7 7 6 6 6 4 .

8 8 a 5 4 3 4 5 7 8 8 8 9 9 910 101010109 7 6 5 6 6 7 8 9 9 9 9 8 8 6 43

097543457899910 10987778910 10109754333

097533357910 10999910 9865433

97533357910 10976543

975434579 10976543

986556689 ~:::":: .• - -20 98 q 7 8 91 0 10 87 P 43 .,. -20~ 1088 7 P 78 9 101

0101 0 9 9!l p!!O tV" H''''' 160 150 1.40 130 120 1;0 100 9'0 80 70 160 ,i i , I

Figure A-3c

Grid sample size and local resolution for surface dynamic height data. For grid points with sufficient observations within a radius of 2 degrees: rV-20 (') or rV-IOO

(*). For grid points with <20 observations within a radius of 2 degrees, number equals radius in degrees within which rV-20. Missing grid points had insufficient

observations within a radius of 10 degrees.
SHIP DRIFT GRIDS

S

0'

c.r,s.

III

fIl

Q.

[

~.

o

.....

i

.,

=

=tl

t')

rJJ

;'

t')

III

i-

::l

III

e:

III

:"! 70

70

80

80

90

90

100

100

110

120 110

120

130

140 130

150 140

150

30--1- + + + + ••••• • .3 •••• +++ •••• ···3.343.+

33 •• +++ •••• 333 •• 33 .... 3++

•• ++++ •• 3333333.3345S4.+

+++++ ••••••••••• 3 3.+++.

20 3 3 3 • + + .. •• 3 •••••••••••••••••••••••• + +' 333333333333.3344333 •••••••• +++

433333333333.34555554433 ••••• +++++

433333334333.3 S 67777788543.3.' ++. ++ ++'

10-13 3 3 3 3 3 3 3 4 3 3 3 3 4 5 8 6 7 8 II g 6 8 6 5 4 3 3 3 ••••• + + +

33344444333335655S55556S433333 ••••••• + ..

3344554433334866685555665433333 ••••••• +++

3 3 4 5 5 4 4 4 4 3 3 4 5 7 9101010101010109 II 8 5 4 3 3 4 4 3 ••••••• + + •

3 4 5 5 4 3 3 4 3 3 3 4 6 6 g 1010109 8 7 7 7 7 6 5 4 3 3 3 3 3 •••• • ••• +

0-15 4 4 4 3 3 3 4 3 3 3 5 7 8 9 8 7 5 4 4 4 4 S 5 4 4 3 3 • • • • • • • • • •

4433333433487118654333433333 ••• 333 •••••

4433334333578988443333333333 •• 333 ••••

4333344334578854333.333333333 ••••• 333.

43334543348844333333334444443 •••• 33333

-10-14 3 3 3 4 4 4 3 3 4 4 4 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 3 3 •• 3 3 4 4 4 4 3 3 • +

333443 •• 3333344443333444433333334444443. +i'

333333.334556865433344543 •• 333333565654 •••

3.33334457887854333344433334444335888543 •• +

3333345688878S443334333334455544456778433.

130 120 110 100 90 80 70 ISO 140

30, . 333 ••••••••• 33 ... 4566 ... +

443 •••••• 3344444456653++

••• + ••• 3344344434558843+

++++ •••••••••• 33 5666543

20-{ .5 3 .. .3

3.3333J333333 ••••••••••• ·.·++' 844433333443334554433 ••••••• +++

7544333444433456788765443 ••• ·.++++

7 5 3 3 3 4 4 4 4 4 4 3 4 4 5 7 9101010108 7 8 4 4 3 3 ••••• + + + +'

10-16544456 6555456781010101010109 7 8 5 4443 •••• + + +

4445566654456677777771765433433 ••••••

43486655545677888777777854334433 •••••• +++.

3 4 5 67 7 8 6 5 5 7 810101010101010101010109 8 7 7 8 5 5 5 3 3 ••••••• + •

6 5 6 6 6 6 6 5 5 6 8 91010101010101010101010108 1 6 5 4 3 3 3 ••••••• • •

O~ 08 7 8 8 6 8 5 7 8 101010 9 109 8 7 8 8 7 7 8 7 8 8 5 4 3 3 3 3 3 3 3 • • • 3 3

1010988777910101010975433458554444445554333335

9 7 6 11 1 8 8 91010109 II 6 4 3 33 4 4 4 4 4 4 4 44 5 5 5 5 5 3 3 4 43 3 5

7 5 5 5 6 67 II 9109 9 8 7 5 4 3 33 4 4 4 5 6 8 7 7 6 6 6 5 4 4 4 4 5 5 4 4 3

7556887999887S43334487899911785445567654 ••

-1 O~ 0 9 7 7 7 7 7 8 7 7 7 6 5 4 4 3 4 4 5 8 7 8 1010 9 8 7 6 5 5 4 5 5 8 7 7 7 6 4 3 •

10977888568886 II 85558789109887655567778 II 6 5 3.

8785S5557899997655S688988766677888898654.

5455878101010101010978546777887888910101010101010986 5 3 •• .18 6 6 8 910101010101010108 6 555568677691010101010101010101010976 4 •• -

-20010101010101010101010101010998768 t 8 910101010101010101010101010101097 i 3 • • 4'

1io i' '"

-10

J A 30 •• ·············.333443. 54.43 •••••••• 34.444455.4.+ un- ug 333 •••• + ••••• 33333.45.4.+

643 •••••• 3.456665551153++ 543 •• ++···333333334553++

.3 ••••• 3455666611888653+ .3. ++ ••• 344433333458643 + •• ++ •••••••• 33345788875 ... ++. .+++ ••••••••••• 335e875 .. 3.++.

20-f.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .3 .3 .. 5 .. .3 .. + .. 20 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 3 .. 4 .. 3 + + + 333333 ...... 444 .. 33 ••••••••• 3 33++ 3.33 •• 333.333 ••••••••• ·.·3.+-+'

154454444565555686543 •••••••• ++ 533333333333333554433 ••••••• +++

86555444555666778888775433 ••••• ++. 5333333333333348776855443 •••• ·++++

108 6 5 8 6 5 5 6 5 5 5 5 6 7 89101010101010109 7 6 4 3 •••• + + + + 8 4 3 4 3 3 3 3 3 3 3 3 3 46 7 8 8 8 8 8 7 7 6 5 4 4 3 3 • • • • + + + +

10-19 1 6 77 8 8 7 1 7 5 5 5 5 5 67 1 8 91010101010109 8 6 5 4 3 ••• + + 10 4 4 4 4 4 4 4 4 3 3 3 3 3 45 5 5 5 5 5 5 5 5 5 5 4 4 3 3 3 •••• + + +

866789987755555555555858555554433.3 •• ++ 334455443333345545555555443333 ••••••• + ..

08 6 7 8 8 8 8 7 7 6 1 7 7 7 8 8 8 8 7 7 1 7 8 5 5 5 5 5 4 4 3 3 3 3 3 3 3 • + + • 3 3 4 4 5 5 4 4 4 4 4 5 5 , 1 8 9109 9 9 9 8 7 6 5 4 3 3 3 3 3 •••••• + + + •

01088888871910101010101010101010101010101010108765433 • 333. 3455544444578.101010101010101010101099875543 • • •• • • • • •

010888887789101010101010101010101010101010986554333 •• 33. • 555444444458191010101010101010109877644443 •••••••

0-19 1 6 6 5 8 6 5 8 7 8 8 9 9 9 9 9 8 8 7 7 1 7 1 8 5 4 3 3 3 3 3 3 3 3 • • • 3 3 0 1 5 5 4 4 4 4 5 5 8 7 8 7 8 8 7 6 5 5 5 5 5 6 6 1 8 5 4 3 3 3 3 3 3 3 • • • 3 3

8554.445445677875444454333333333333 ••••• 4 8655555578998864433444444444444554433335

4 4 3 4 4 5 5 4 3 4 5 8 7 8 5 4 3 3 3 4 3 3 3 3 3 3 333 3 3 3 3 ••• 3 •• 4 9 7 8 5 8 8 6 8 8 9109 8 7 6 4 3 3 4 4 4 4 4 4 4 4 .4 4 45 5 5 5 4 4 4 4 4 8 8

44344544456765433333333344443.333.334333 9766786789888654333344555555555554558643

5 4 3 4 4 5 4 4 5 5 6 5 4 3 3 3 3 3 3 3 4 5 5 5 4 4 4 4 3 3 3 3 3 4 4 5 4 4 3 • • 9 7 6 8 7 8 7 7 8 II 7 7 5 5 4 3 3 3 3 4 5 5 8 7 8 8 8 8 8 8 5 5 6 7 7 7 7 5 4 ••'

5 4 3 4 5 4 4 4 4 4 4 4 3 3 3 3 3 4 5 5 8 6 5 5 4 4 4 4 3 3 3 3 4 5 6 5 5 4 3 • • -10 09 7 II 7 8 8 8 8 7 6 8 5 4 4 4 4 4 5 8 8 7 7 7 1 7 8 8 5 5 5 6 8 II 9 9 7 6 4 3 •

,.4 3 3 4 4 3 3 3 3 3 3 3 3 4 4 4 5 5 6 5 5 5 5 5 5 4 4 3 3 3 3 4 5 6 7 7 8 5 4 3 • • 010 II 7 8 5 8 8 8 6 6 8 6 8 6 5 5 5 8 8 8 7 7 7 7 8 6 5 5 5 8 8 7 II 9 9 8 8 5 3 • •

3 3 3 3 3 3 3 3 3 4 5 5 6 6 5 5 5 4 4 5 5 5 5 5 4 4 4 4 4 4 4 5 5 7 7 8 8 6 4 4 8 8 8 5 5 4 4 4 5 6 7 II II 7 6 5 4 4 4 5 6 1 7 7 7 7 6 5 6 6 7 II 9 9109 8 6 6 4 ••

3 333 3 3 .. 5 7 8 9 8 7 8 4 4 .. 4 4 5 5 5 5 4 4 4 5 5 8 8 5 8 7 8 8 8 8 7 5 4 3 • • 5 4 4 5 5 5 5 6 8 9 9 9 8 8 7 5 4 4 5 5 6 7 7 7 7 7 7 II 8 9 9 91010109 II 7 8 53 ••

3444557899117544344555444556876678888 II 7653. 756671110101010998666666766677119910101010101010101097 643. '-

-20 -20 • •

160 150 1.40 130 120 110 100 90 80 70 160

Figure A-3d

Grid sample size and local resolution for ship drift data. For grid points with sufficient observations within a radius of 2 degrees: ~100 (*) or ~500 (+). For grid

points with <100 observations within a radius of 2 degrees. number equals degrees of longitude within which ~100.

-
22 NOAA Technical Report NMFS 109

10.0

p

--'

CD..:::a

....

aJ

..

CD

a.

E 1.0

CD

U

aJ

....

..:::a

(I)

-

Q

(I)

0.1

10 100

N

1000 10000

Figure A-4a

Standard deviation (SD) versus sample size (N) in seasonal grids of surface temperature. Solid lines

represent corresponding standard errors (SD/VN) of the grid means.
100

E

.. -.c

....

Q,

CD

Q

..

CD

.,>- 10

..J

'U

CD

:IE

-

Q

(I)

1

Fiedler: Climatologies and Variability of Eastern Pacific Surface Waters 23

E

.c

....

Q,

CD

Q

CD

c

- 10 U

0

E..

CD

.c

to-

-

Q

(I)

10 100

N

1000 10000

FigureA-4b

Standard deviation (SD)

versus sample size (N) in

seasonal grids of mixed

layer depth (top) and

thermocline depth (bottom). Solid lines represent

corresponding standard

errors (SD/"N) of the

grid means.
24 NOAA Technical Report NMFS 109

Figure A-4c

Standard deviation (SD)

versus sample size (N) in

seasonal grids of surface salinity (top) and surface

dynamic height (O/500db,

bottom). Solid lines represent corresponding standard

errors (SD/--JN) of the grid

means.

1000

N

100

10.00

0.01

100

E

()

c

>- 'U

.c

OJ

'i

::c

.2

E 10

II

C

>- Q

•()

CD -..::::I

U)

-

Q

U)

1

10

::::I

•

a.

-

- 1.00 >-

C

-

'i

U)

4»

()

CD -..::::I

U) 0.10

-

Q

U)
.. 50 I

to

E

u

... ..

...-

C

Q.

:c

UJ

'0

..

<G

...

I)

<G

W

-

C

UJ

10

Fi~dler: Climatologies and Variability of Eastern Pacific Surface Waters 25

50 I

I)

E

u

... ..

-..

C

Q.

:c

o

'0

..

G

.c

.....

o

z

-

10 100

N

1000 10000

FigureA-4d

Standard deviation (SD)

versus sample size (N) in

seasonal grids of ship

drift. Solid lines represent

corresponding standard

errors (SD/-VN) of the

grid means.
26 NOAA Technical Report NMFS 109

SURFACE TEMPERATURE

20

10

-10

-20160 150 uo 130 120 110 100 eo 80 70

SURFACE SALINITY

301ll111i11

20

10

o

-10

Figure A-5

Annual c1imatologies of surface temperature (0C), from 1960-1990 bathythermograph data, and surface

salinity (psu), from 1960-1988 hydrographic data.
Fiedler: Climatologies and Variability of Eastern Pacific Surface Waters 27

MIXED LAYER DEPTH

150 140 130 120 110 100 iO 80 70

o

20

10

-10

-20+--_-,..--_-"r'--_-...--_...c;;.'T""'"-..,..I.-'T""'"-_-r--_......r--

160

THERMOCLINE DEPTH

CCR10

CCT

ER 0

-10 1'--_

SET

-2~i6":'0-~-1':"50r:------'1'r40----1"'!3-0-~~..,..--.....I,....,......a.._ ...-1"TOO.l........l.".....J.;;...,iOr----..;;;;;;;11'"0=;;;;;;;;;;="'7+0

FigureA-6

Annual climatologies of mixed layer depth (m) and thermocline depth (20°C isotherm depth, m), from 1960-

1990 bathythermograph data. For thermoclins: depth, NET = North Equatorial Trough; CCR = Countercurrent

Ridge; CCT =Countercurrent Trough; ER = Equatorial Ridge; SET =South Equatorial Trough.
28 NOAA Technical Report NMFS 109 _

THERMOCLINE STRENGTH

130 120 110 to 80 70

"""'---_---_-1.0---- _

140

...

O.k

L•••_).-..::_-1.0 ,••.••,I.••:,.':,.•.:, '"...•.:.:!,.••.•.i...•.:;.,•...•.:;..•...:,.•.•.• ;..•.'..•....•.•.•.. ,:,5.•,i.!,·i.,L.i.f.

1I

.i.:.i..:.••.::.••.••: ,i.•.•.:.••.•.•.•.•.:.'.:.•.:.•.•.•.:.•.:.:.•.:.•.;.•.•.:.•.:.:.:.i.i.: '.:.?' •• ::::::::;::::::::::;::<::: frrrrr~~r~ ~~ ?:~:~~~:r~:~::;:;::::::::::::::;':<':""" ",'

20 .~to

50+---.....L---........--.......---............."

-20+--...,..;::l""""T-O::;=-"'r--...,;..---r----r--.-----r----r--.--.:-,.-_.-;.......-~'""

160 150

-10

FigureA-7

Annual climatology of thermocline strength (OC 10m-I between 20° and 15°C isotherms), derived from

1960-1990 bathythermograph data.
Fiedler: Climatologies and Variability of Eastern Pacific Surface Waters 29

SURFACE DYNAMIC HEIGHT

30

20

10

o

-10

-20

160 150 uo 130 120 110 100 00 80 70

SURFACE CURRENTS

110 so 70

, .

130 120

, ,

150 140

~------------------ - . . .. ,

- • , - • .. .. • • • , , I I I

l-.................__....._~~~--~--------- - - .. . . .. .. .. .. • , ~-

-..:::-" • • • - p - - - - - - - - - ---- ...............

10 .................... ---....-.." ........... , , • " " .. ,. ......... ..... -..------~~

/,~~/~/~~///~~-~-------~_.# •• ,.---"

//~////////~~/~~~~~~///~~~~----~ ~,~ /

"""--........................................""".........." ................................................ """,,,, \ \ , , , , , ". , ,ii, ~~~~!;'~~----------....... ......._-- .. o+-------------------~---:::----=-----~-.......- ....... , ... -~-'" ......---------_...._.....,-----------..~ "

"-

:::--...-::::..... =~~ < -- "

:c--,.,.-,..------....-----.-;- '$ .... _"""$0.... ---.............. " ////,,///~~--~--~-~~.~ -~-..,'

~~~-----~~~~~~~~~,..-~~~- ---~~ ,',' ------~~~~~~~~/~~--~~~~~~~~~ -~~, ,',' - - I' '-'.- __ -_~._._._",,.,I""" "..,.,.......-.- ....-...-"...,..".,..- --- " , "

-, ... ". _..- _.- - -..- .... ,'/."/.-------.-.-.-------------- """",,, '"

20

-10

FigureA-8

Annual climatologies of surface dynamic height (relative to 500 db, dyn cm), from 1960-1988 hydrographic data, and surface current velocity, from 1900-1969 ship drift reports.
30 NOAA Technical Report NMFS 109

SURFACE CURRENT DIVERGENCE

10

o

-10

-20~·@22~~~*~.L,...--L-r--_~-L2$::iiLJ. 160 140 130 120 110 100 eo

UPWELLING VELOCITY

10

o

-10"---

80 70

FigureA-9

Annual c1imatologies of surface current divergence (10-6 S-I), derived from 1900-1969 ship drift reports,

and upwelling velocity (10-3 cm S~I), calculated from divergence of horizontal transports in the mixed

layer.
Fiedler: Climatologies and Variability of Eastern Pacific Surface Waters 31

SURFACE WINDS

130 120 110 100 90 80 70

-----'- ......... """",

150 uo

-..-._-

........ -... ......-_........ _'--

----------///////111\\ ------~~////I/I/\\\

---------///////1/1/1\\

-.;--------////////1//111

.......-------/////////1/ / II

::----------///////// /11//

::--_------/////////////11 11 "

~----_////////////////"

~~~~~~~~~~~~~~~~----_ .. 10 ------~~.~~- 1------------------ _____________ """ ...... """" , ,'\ '\,,,,, , , , , 11 ,!

----------- ,""""'\'" \ \

------------------- ----""""""\\, \ I 1 , I 1 o+---~----------------- ,',,,,,,,,, ,~ \I I ,

~---~-------------- ,""""""''\-\.\\ \ I I--._------~-----------_.........,"""""'"'\ \\\\ ------------------_ "" "'" ""

,\ \ \ -----~----:----------------_ """""""

,\ --------------~--_-.:..._---------_ ,''''''''''' \. \ -----~-------------------, """"""

\ '\ ------------------ ,

"""""", ----------~-------""""" '\ -------......."",,\\\\

20

-10

WIND DIVERGENCE

30+------:

20

o

-10

90 80 70

-20+----,..----.......r----t=~~=t"=~=¥=~='F=~~F~~"'4=~=_+

160 150 1AO 130 120 110 100

FigureA-I0

Annual ciimatologies of surface wind velocity and wind divergence (10-6 sec-I), from 1961-1989 Florida

State University monthly gridded fields of pseudostress. The band of strong negative divergence along

looN is the intertropical convergence zone (ITCZ).
32 NOAA Technical Report NMFS 109

WIND STRESS

140 130 120 110 100 llO 80 70

...

150

10

30

20

-10

-20

160

ZONAL/TOTAL WIND STRESS

Figure A-II

Annual climatology of surface wind stress (dyne cm-2) and ratio of zonal to total wind stress in annual

climatologies, from 1961-1989 Florida State University monthly gridded fields of pseudostress.
Fiedler: Climatologies and Variability of Eastern Pacific Surface Waters 33

WIND STRESS CURL

120 110 100 90 80 70

10

20"'1.-__....

3O+----......---......---......---r..........,....................,__

o

-20+----r

160

-10

EKMAN PUMPING VELOCITY

110 100 90 80 70

..................................... .

-0.'

-0.5

-----------------------------------~~----

...•

o ..

10 l-:::===::o:~::=:::=.:~!...=:::::::::==:: I- -0.2-

-----0.5··.,..,··,..,.,··.,.,.···,.,.,··",···.,.,.···,.,.,··-.·.,.,.···=··.,.,., .. ·-- .

20

-10---..

-0.2

-0.1 -20t---":"'!":'---:'r-------,~~==:;::==--....,....--...,..-~~--I.~-r--_ 160 1~ 1~ 130 1~

Figure A-12

Annual c1imatologies of surface wind stress curl (10-8 dyne cm-3 ) and Ekman pumping velocity (10-3 cm

S-I), derived from 1961-1989 Florida State University monthly gridded fields of pseudostress. Ekman

pumping velocity is undefined within 6 degrees of the equator.
(,>0

,j>.

SURFACE TEMPERATURE

z

30 I loa , ot:: , < <: , <: , .... ! I I I 0

,., 20~ ... ~---- ~-""""""/. ~-..-r 20~ -....~J __ -i(~__ ~/ ~:.-I- I - [

,.,

a

10-t<"," "., .... :""":,. "",,.,.,<,,,,,)ll::«:""': »::/", »<;;;;;;17""":,:',~:>~ .-.. 10~'<'" .'."',',',',',':~~~.<.':.:":",,.,,,,.,.,,,,:,:::::/:::::' :':':":,:";<' }':':':}"::':::':}}}:{{{{:~:::Y:~:~~ .-.. I 'tl

0.,

...

Z

o+",+s~,<:",+",~;;;<-;;~s~",,,,~ - - -~~;;;;;;; O+''''''':+''':',",:''':''':''':S~""",,,,F,,,':';-::''':';'''''''~::,,,:,,,:,,,:,,,o,;,,,,'',",c:+:lit£4~:,",,",,··

rJl

....

Q

.-.-, ...-...........-....-.-.-...;..........=... _.-.- ..-.-,-.-'."",,,-" .......... . .;" ---...,_.~.~ .~ ,.--- .......'........................,........,............·c·.·.·.·.·.·........................'..........:a •.•• .. ......1. .......•.•.•.•...•.•.•.•.•••...•.-;..;_..~._._; ;.," 111111'1.___

-10

-20

1&0 150 , ..0 130 120 110 100 90 80 70 160 150 , ..0 130 120 110 100 90 80 70

30 30 Jun-Aug

20 .. :- 20

10

0

-10

-20

1&0 150 , ..0 130 120 110 100 90 80 70 160 150 , ..0 130 120 110 100 90 80 70

Figure A-13a

Surface temperature seasonal c1imatologies (0C), from 1960-1990 bathythermograph data.
SURFACE TEMPERATURE - SEASONAL DEVIATIONS

30 30

20 20

10 10

0 0

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I'

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Figure A-20b

Surface current divergence seasonal deviations from annual climatology (10-6 S-I), iD

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Figure A-21a

Upwelling velocity seasonal c1imatologi"es (l0-3 cm S-I), calculated from divergence of horizontal transports in the mixed layer.
UPWELLING VELOCITY - SEASONAL DEVIATIONS

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Figure A-21b

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SURFACE WINDS SEASONAL DEVIATIONS

Figure A-22b

Surface wind velocity seasonal deviations from annual climatology.

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Figure A-23a

Surface wind divergence seasonal climatologies (10-6 S·l), derived from 1961-1989 Florida State University monthly gridded fields of pseudostress.
WIND DIVERGENCE - SEASONAL DEVIATIONS

30

20

10

0

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Figure A-23b

Surface wind divergence seasonal deviations from annual climatology (l0-6 S-I). ...

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WIND STRESS

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100

100

110

110

120

120

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140

150

150

o

o

10

20

-10

-10

80 70

Jun-Aug , '

150 140 130 120 110 100 90

o

30 I \' 7' _' '",.

20-1 -. -

Figure A-24b

Surface wind stress seasonal deviations from annual climatology (dyne cm-2) ,

10T:::::::::::':'::C":"""":':~

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160 150 140 130 120 lID 100 90 80 70 160

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z

...

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Figure A-25a

Wind stress curl seasonal c1imatologies (l0-8 dyne cm-3) , derived from 1961-1989 Florida State University monthly gridded fields of pseudostress.
WIND STRESS CURL - SEASONAL DEVIATIONS

20

10 10

0 0

-10 ~~',:",:;;;;;;/,,:\ J<-- <"""""""""""""""""""""':""'?~ X"""N':"""'?l'tr:-.-

:;J

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Figure A-25b

Wind stress curl seasonal deviations from annual climatology (10-8 dyne cm-3). ...

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EKMAN PUMPING VELOCITY o

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o

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-20

180

150 1040 130 120 110 100 90 80 70

20~ ......

30~ b '<.-!:.. 'I

10·'·'·'·,..······

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o+:----------------------------~~---

30 I '}! , , ' .. j

Figure A-26a

Ekman pumping velocity seasonal climatologies (10-3 cm S-I), derived from 1961-1989 Florida State University monthly gridded fields of pseudostress.
EKMAN PUMPING VELOCITY - SEASONAL DEVIATIONS

~-o.'

20b

301 "'......j i I I .....,II1II

1°-G: ~:.~' .•rr·:~

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160 150 140 130 120 110 100 90 60 70 160 150 140 130 120 110 100 90 80 70 :l

C"l

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Ekman pumping velocity seasonal deviations from annual climatology (10-3 cm S-I). ....

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....

Fiedler: Climatologies and Variability of Eastern Pacific Surface Waters 63

MIXED LAYER DEPTH VARIABILITY

30

20

10 :.:::.:

-10

-20

160

30

20

o

-10

20

10

110 100 110 80

70

70

FigureA-28

Mixed layer depth

variability (standard de-,

viation, m) between

bimonths (seasonal) and

between years (interannual), from 1960-1989

bathythermograph data.
64 NOAA Technical Report NMFS 109

THERMOCLINE DEPTH VARIABILITY

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Figure A-29

Thermocline depth variability (standard deviation, m) between bimonths (seasonal) and

between years (in terannual) , from 1960-1989

bathythermograph data.

120 110 100 110 80 70

....~---

130

............

10

10

o

20

10

-10

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160 150 140 130 120 110 100 ~O 80

30

-10
Fiedler: Climatologies and Variability of Eastern Pacific Surface Waters 65

WIND STRESS VARIABILITY

-20,~~~~~~ 160 1~ 130 120 110 100 110 80 70

Interannual

30

20

10

o

-10

160

30

20

10

-10

-20160

30T0J0lITITMm'!fl7.

20

10

o

-10

110 80 70

70

Figure A-30

Wind stress variability

(standard deviation, dyne

cm-2) between bimonths

(seasonal) and between

years (interannual), from

1961-1989 Florida State

University monthly gridded fields of pseudostress.